The complexity of quantum support vector machines

Understand

Quantum support vector machines employ quantum circuits to define the kernel function.

• It has been shown that this approach offers a provable exponential speedup compared to any known classical algorithm for certain data sets.
• The training of such models corresponds to solving a convex optimization problem either via its primal or dual formulation.
• Due to the probabilistic nature of quantum mechanics, the training algorithms are affected by statistical uncertainty, which has a major impact on their complexity.